Yonas Demissie

• Ph.D. in Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 2008
• M.S. in Hydrology and Water Resource Engineering, Katholieke Universiteit Leuven and Vrije Universiteit Brussel, Belgium, 2001
• B.S. in Agricultural Engineering, Haramaya University, Ethiopia, 1998

Joined WSU Tri-Cities in 2012 from Argonne National

• Characterization of  surface and subsurface hydrology
• Inverse modeling and stochastic hydrology
• Hydrological and water quality modeling
• Data mining and assimilation
• Optimizing hydraulic and hydrologic designs
• Renewable energy and climate change impacts on hydrology
• Assessment of water resources sustainability under natural and human induced changes and uncertainties

• Moges, E., Y. Demissie, and H. Li, 2015, Structural Uncertainty Diagnostics: A Case of Two Catchments under Hierarchical Mixture of Experts, Water Resources Research (accepted)
• Mortuza, R., Y. Demissie, H. Li, 2014. Regional frequency and Bayesian uncertainty analyses of extreme precipitation in Bangladesh, Journal of hydrology (in revision).
• Demissie, Y., E. Yan, Implications of future biofuel feedstock production scenarios on hydrology and water quality in Ohio River Basin, Journal of hydrology (in review).
• Ye S., H. Li, S. Li, L.R. Lenug, Y.Demissie, Q. Ran, G. Blöschl, 2015. Vegetation regulates streamflow intra-annual variability by adapting to climate variations, Geophysical Research Letters, doi:10.1002/2015GL066396.
• Li S., L. Xiong, H. Li, L.R. Leung, Y. Demissie, 2015. Attributing runoff changes to climate variability and human activities: Uncertainty analysis using four monthly water balance models, Stochastic Environmental Research and Risk Assessment, doi: 10.1007/s00477-015-1083-8
• Senay, G.B., S. Bohms, N.M. Velpuri, Y. Demissie, M. Gebremichael, 2014. Understanding the hydrologic sources and sinks in the Nile Basin: Using multi-source climate and remote sensing datasets, Water Resources Research, DOI: 10.1002/2013WR015231.
• Demissie, Y., A. Valocchi, X. Cai, N. Brozovic, M. Gebremichael, G. Senay, 2014. Parameter estimation of groundwater models under uncertain irrigation data, Groundwater, DOI: 10.1111/gwat.12235.
• Yan, E., Y. Demissie, M. Wigmasta, V. Tidwell, C. King, 2013. Potential drought impacts on electricity generation in Texas, Proceedings of the ASME 2013 Power Conference, Power2013-98318.
• Demissie, Y., E. Yan, and M. Wu, 2012. Assessing Regional Hydrology and Water Quality Implications of Large-Scale Biofuel Feedstock Production in the Upper Mississippi River Basin, Environmental Science & Technology, DOI: 10.1021/es300769k.
• Wu, M., Y. Demissie, and E. Yan, 2012. Simulate impacts of future biofuel production on water quality and water cycle dynamics in the Upper Mississippi River Basin, Biomass and Bioenergy, DOI: 10.1016/j.biombioe.2012.01.030.
• Demissie, Y., E. Yan, and M. Wu, 2012. Effects of biofuel productions in the Ohio River basin’s water resources and quality. In: Environmental Science and Technology, G. Sorial and J. Hong, Eds. American Science Press, Houston, USA, 2012, Vol. 2, p. 577-582. ISBN: 9780976885344.
• Wu, M., Y. Chiu, and Y. Demissie, 2012. Quantifying the regional water footprint of biofuel using multiple analytical tools, Water Resources Research, DOI:10.1029/2011WR011809.
• Demissie, Y., A. Valocchi, B. Minsker, and B. Bailey, 2009. Integrating a calibrated groundwater flow model with error-correcting data-driven models to improve predictions, Journal of hydrology, DOI: 10.1016/j.jhydrol.2008.11.007
• Demissie, Y., A. Valocchi, B. Minsker, and B. Bailey, 2008. Bias-corrected groundwater model prediction uncertainty analysis. In: J. Refsgaard (Editor), Calibration and Reliability in Groundwater Modeling: Credibility in Modeling, IAHS Publ. 320.